Library & Dataset

Using OLR

Inspect Dataset Using Training and Validation

OLR Equations

Inspect Dataset Using Training and Validation

vclust <- varclus (~angle+brick+wood+mixed+ density+EN +TC + TC_mature_soil + TC_saprolite_soil +  TC_weath_rock  + TC_unstable_structure  + T_construction  + spring +  landfill + garbage  + crack + leaning_wall + scars + downward_floor + tilted + fracture + conc_rainfall + wastewater + leak + septic_tank  + tree + ground_veg + deforestation + banana + drainage , data=train.data)

# took out density since training has 0 d4 and it was not allowing do the plot

p <- plot(vclust)

par(mfrow=c(6,5))
plot.xmean.ordinaly (risk~angle+brick+wood+mixed+ density+EN +TC + TC_mature_soil + TC_saprolite_soil +  TC_weath_rock  + TC_unstable_structure  + T_construction  + spring +  landfill + garbage  + crack + leaning_wall + scars + downward_floor + tilted + fracture + conc_rainfall + wastewater + leak + septic_tank  + tree + ground_veg + deforestation + banana + drainage, data=train.data, cr=TRUE , subn=FALSE)

#angle + building+density+EN +TC + TC_mature_Soil + TC_saprolito +  TC_weath_rock + TC_rock + TC_geol_desfav + Taterro + DepEncNatural + DepTaludeAterro + DepTaludeCorte + DepTaludeAterro + aterro + lixo + entulho + crack + belly_wall + scars + drawback + tilted + fracture + conc_rainfall_water + wastewater + leak + septic_tank + drainage + tree + ground_veg + deforestation + banana 

Diagnostic 2: Proportion (-5% of one of the parameters based on what is expected. Since some parameters have 2 predictors, others 5)

#library(plyr)
brick <- count(train.data$brick) %>% 
  mutate ("Percentage"=(freq/265)*100)%>%
  mutate("Classifier" = "brick")

wood <- count(train.data$wood) %>% 
  mutate ("Percentage"=(freq/265)*100)%>%
  mutate("Classifier" = "wood")

mixed <- count(train.data$mixed) %>% 
  mutate ("Percentage"=(freq/265)*100)%>%
  mutate("Classifier" = "mixed")

TC_mature_soil <- count(train.data$TC_mature_soil) %>%
  mutate ("Percentage"=(freq/265)*100)%>%
  mutate("Classifier" = "TC_mature_soil")

T_construction  <- count(train.data$T_construction ) %>%
  mutate ("Percentage"=(freq/265)*100) %>%
  mutate("Classifier" = "T_construction ")

spring <- count(train.data$spring) %>%
  mutate ("Percentage"=(freq/265)*100)%>%
  mutate("Classifier" = "spring")

landfill <- count(train.data$landfill) %>%
  mutate ("Percentage"=(freq/265)*100)%>%
  mutate("Classifier" = "landfill")

garbage <- count(train.data$garbage) %>%
  mutate ("Percentage"=(freq/265)*100)%>%
  mutate("Classifier" = "garbage")

crack <- count(train.data$crack) %>%
  mutate ("Percentage"=(freq/265)*100)%>%
  mutate("Classifier" = "crack")

leaning_wall <- count(train.data$leaning_wall) %>%
  mutate ("Percentage"=(freq/265)*100)%>%
  mutate("Classifier" = "leaning_wall")

scars <- count(train.data$scars) %>%
  mutate ("Percentage"=(freq/265)*100)%>%
  mutate("Classifier" = "DepTaludeAterro")

downward_floor <- count(train.data$downward_floor) %>%
  mutate ("Percentage"=(freq/265)*100)%>%
  mutate("Classifier" = "scars")

tilted <- count(train.data$tilted) %>%
  mutate ("Percentage"=(freq/265)*100)%>%
  mutate("Classifier" = "tilted")

conc_rainfall <- count(train.data$conc_rainfall) %>%
  mutate ("Percentage"=(freq/265)*100)%>%
  mutate("Classifier" = "conc_rainfall")

wastewater <- count(train.data$wastewater) %>%
  mutate ("Percentage"=(freq/265)*100)%>%
  mutate("Classifier" = "wastewater")

leak <- count(train.data$leak) %>%
  mutate ("Percentage"=(freq/265)*100)%>%
  mutate("Classifier" = "conc_rainfall_water")

septic_tank <- count(train.data$septic_tank) %>%
  mutate ("Percentage"=(freq/265)*100)%>%
  mutate("Classifier" = "septic_tank")

angle <- count(train.data$angle) # angle A less than 5% but the rest are okay (3,50, 91, 277, 109) Expected=106
angle <- angle %>%
  mutate("Percentage"=(freq/106)*100)%>%
  mutate("Classifier" = "angle")

EN <- count(train.data$EN) %>%
  mutate ("Percentage"=(freq/265)*100)%>%
  mutate("Classifier" = "EN")

TC <- count(train.data$TC)  %>%
  mutate ("Percentage"=(freq/265)*100) %>%
  mutate("Classifier" = "TC")

TC_saprolite_soil  <- count(train.data$TC_saprolite_soil )  %>%
  mutate ("Percentage"=(freq/265)*100)%>%
  mutate("Classifier" = "TC_saprolite_soil ")

banana <- count(train.data$banana) %>%
  mutate ("Percentage"=(freq/265)*100)%>%
  mutate("Classifier" = "banana")

drainage <- count(train.data$drainage) %>%
  mutate ("Percentage"=(freq/176.7)*100)%>%
  mutate("Classifier" = "drainage")

deforestation <- count(train.data$deforestation) %>%
  mutate ("Percentage"=(freq/265)*100)%>%
  mutate("Classifier" = "deforestation")

TC_unstable_structure  <- count(train.data$TC_unstable_structure ) %>%
  mutate ("Percentage"=(freq/265)*100)%>%
  mutate("Classifier" = "TC_unstable_structure ")


tree <- count(train.data$tree) %>%
  mutate ("Percentage"=(freq/265)*100)%>%
  mutate("Classifier" = "tree")

ground_veg <- count(train.data$ground_veg) %>%
  mutate ("Percentage"=(freq/265)*100)%>%
  mutate("Classifier" = "ground_veg")


density <- count(train.data$density)  %>% #(79, 415, 36) # d4 =0 
  mutate ("Percentage"=(freq/132.5)*100)%>%
  mutate("Classifier" = "density")

TC_weath_rock  <- count(train.data$TC_weath_rock ) %>%
  mutate ("Percentage"=(freq/265)*100)%>%
  mutate("Classifier" = "TC_weath_rock ")

fracture <- count(train.data$fracture) %>%
  mutate ("Percentage"=(freq/265)*100)%>%
  mutate("Classifier" = "fracture")









df <- rbind(brick, wood, mixed, TC_mature_soil, T_construction, spring, landfill, garbage, crack, leaning_wall, scars, downward_floor, tilted, conc_rainfall, wastewater, leak, septic_tank, angle, EN, TC, TC_saprolite_soil,  banana, drainage, deforestation, TC_unstable_structure, tree, ground_veg,density, TC_weath_rock, fracture)

df
##        x freq  Percentage             Classifier
## 1  FALSE   38  14.3396226                  brick
## 2   TRUE  492 185.6603774                  brick
## 3  FALSE  457 172.4528302                   wood
## 4   TRUE   73  27.5471698                   wood
## 5  FALSE  490 184.9056604                  mixed
## 6   TRUE   40  15.0943396                  mixed
## 7  FALSE  256  96.6037736         TC_mature_soil
## 8   TRUE  274 103.3962264         TC_mature_soil
## 9  FALSE  209  78.8679245        T_construction 
## 10  TRUE  321 121.1320755        T_construction 
## 11 FALSE  512 193.2075472                 spring
## 12  TRUE   18   6.7924528                 spring
## 13 FALSE  320 120.7547170               landfill
## 14  TRUE  210  79.2452830               landfill
## 15 FALSE  352 132.8301887                garbage
## 16  TRUE  178  67.1698113                garbage
## 17 FALSE  437 164.9056604                  crack
## 18  TRUE   93  35.0943396                  crack
## 19 FALSE  501 189.0566038           leaning_wall
## 20  TRUE   29  10.9433962           leaning_wall
## 21 FALSE  330 124.5283019        DepTaludeAterro
## 22  TRUE  200  75.4716981        DepTaludeAterro
## 23 FALSE  459 173.2075472                  scars
## 24  TRUE   71  26.7924528                  scars
## 25 FALSE  430 162.2641509                 tilted
## 26  TRUE  100  37.7358491                 tilted
## 27 FALSE   17   6.4150943          conc_rainfall
## 28  TRUE  513 193.5849057          conc_rainfall
## 29 FALSE  204  76.9811321             wastewater
## 30  TRUE  326 123.0188679             wastewater
## 31 FALSE  338 127.5471698    conc_rainfall_water
## 32  TRUE  192  72.4528302    conc_rainfall_water
## 33 FALSE  526 198.4905660            septic_tank
## 34  TRUE    4   1.5094340            septic_tank
## 35     C   30  28.3018868                  angle
## 36     D  130 122.6415094                  angle
## 37     E  370 349.0566038                  angle
## 38 FALSE  337 127.1698113                     EN
## 39  TRUE  193  72.8301887                     EN
## 40 FALSE   28  10.5660377                     TC
## 41  TRUE  502 189.4339623                     TC
## 42 FALSE  445 167.9245283     TC_saprolite_soil 
## 43  TRUE   85  32.0754717     TC_saprolite_soil 
## 44 FALSE  355 133.9622642                 banana
## 45  TRUE  175  66.0377358                 banana
## 46     Y   70  39.6151669               drainage
## 47     P  227 128.4663271               drainage
## 48     N  233 131.8619128               drainage
## 49 FALSE  494 186.4150943          deforestation
## 50  TRUE   36  13.5849057          deforestation
## 51 FALSE  518 195.4716981 TC_unstable_structure 
## 52  TRUE   12   4.5283019 TC_unstable_structure 
## 53 FALSE  204  76.9811321                   tree
## 54  TRUE  326 123.0188679                   tree
## 55 FALSE  154  58.1132075             ground_veg
## 56  TRUE  376 141.8867925             ground_veg
## 57    d1   66  49.8113208                density
## 58    d2  423 319.2452830                density
## 59    d3   41  30.9433962                density
## 60 FALSE  519 195.8490566         TC_weath_rock 
## 61  TRUE   11   4.1509434         TC_weath_rock 
## 62 FALSE  529 199.6226415               fracture
## 63  TRUE    1   0.3773585               fracture

TC_weath_rock, TC_rock_TC_geol_desf, fracture, TC_rock

Equation 1

f1 <- lrm(risk ~ building + EN + TC_saprolito + Taterro + DepEncNatural + DepTaludeAterro + DepTaludeCorte + landfill + garbage + construction_deposit + crack + leaning_wall + scars + downward_floor +tilted + conc_rainfall_water + wastewater + leak + tree + ground_veg + banana , data=train.data, x=TRUE , y=TRUE)

f1 <- lrm(risk ~ building + EN + TC_saprolito + Taterro + DepEncNatural + DepTaludeAterro + DepTaludeCorte + landfill + garbage + construction_deposit + crack + leaning_wall + scars + downward_floor +tilted + conc_rainfall_water + wastewater + leak + tree + ground_veg + banana + septic_tank +TC_mature_Soil , data=train.data, x=TRUE , y=TRUE) print (f1 , latex =TRUE , coefs =5) stargazer(anova(f1), type=“text”, style=“default”)

# Equation 1

eq_OLR_01 <- polr(risk ~ brick+ wood+ EN +  TC_mature_soil + T_construction + spring+ landfill+ leak+ garbage+ crack+ leaning_wall+ scars+ downward_floor+ tilted+ septic_tank+ conc_rainfall+ wastewater+ ground_veg + angle + TC_saprolite_soil, data= train.data
           ,  method = "logistic", Hess = TRUE)
ctable <- coef(summary(eq_OLR_01))



p<- pnorm(abs(ctable[, "t value"]), lower.tail = FALSE*2) #computes p value
ctable <- cbind(ctable, "p value" = p )

ctable
##                             Value Std. Error    t value      p value
## brickTRUE             -1.23000934  0.4483678 -2.7433044 3.041213e-03
## woodTRUE               1.47754296  0.3379025  4.3726898 6.136252e-06
## ENTRUE                 0.89306822  0.3655888  2.4428218 7.286466e-03
## TC_mature_soilTRUE     0.89154757  0.2262856  3.9399214 4.075416e-05
## T_constructionTRUE     0.25595644  0.3586244  0.7137174 2.377010e-01
## springTRUE            -0.28875964  0.6549612 -0.4408806 3.296497e-01
## landfillTRUE           0.28607107  0.3282531  0.8714953 1.917419e-01
## leakTRUE              -0.32568687  0.2347954 -1.3871090 8.270427e-02
## garbageTRUE           -0.06251049  0.2838820 -0.2201988 4.128582e-01
## crackTRUE              2.07939129  0.3184355  6.5300231 3.287978e-11
## leaning_wallTRUE       1.76143078  0.5242220  3.3600854 3.895919e-04
## scarsTRUE              3.68085510  0.3461251 10.6344647 1.030041e-26
## downward_floorTRUE     0.89483015  0.3556057  2.5163552 5.928780e-03
## tiltedTRUE             1.07445922  0.3251058  3.3049524 4.749627e-04
## septic_tankTRUE       -0.16810143  1.2716056 -0.1321962 4.474146e-01
## conc_rainfallTRUE      1.90437871  0.5794016  3.2868025 5.066593e-04
## wastewaterTRUE         0.72341968  0.2401895  3.0118701 1.298218e-03
## ground_vegTRUE         0.84950619  0.2545000  3.3379414 4.220077e-04
## angleD                 0.58256381  0.4842728  1.2029661 1.144947e-01
## angleE                 0.81651233  0.5470472  1.4925812 6.777343e-02
## TC_saprolite_soilTRUE  0.25169902  0.2921906  0.8614207 1.945032e-01
## R1|R2                  0.99571541  0.9079201  1.0966994 1.363864e-01
## R2|R3                  5.33179526  0.9582739  5.5639574 1.318622e-08
## R3|R4                 10.38907780  1.0513220  9.8819180 2.493457e-23
stargazer((ctable), type="text", style="default", digits = 2)
## 
## ======================================================
##                       Value Std. Error t value p value
## ------------------------------------------------------
## brickTRUE             -1.23    0.45     -2.74   0.003 
## woodTRUE              1.48     0.34     4.37   0.0000 
## ENTRUE                0.89     0.37     2.44    0.01  
## TC_mature_soilTRUE    0.89     0.23     3.94   0.0000 
## T_constructionTRUE    0.26     0.36     0.71    0.24  
## springTRUE            -0.29    0.65     -0.44   0.33  
## landfillTRUE          0.29     0.33     0.87    0.19  
## leakTRUE              -0.33    0.23     -1.39   0.08  
## garbageTRUE           -0.06    0.28     -0.22   0.41  
## crackTRUE             2.08     0.32     6.53      0   
## leaning_wallTRUE      1.76     0.52     3.36   0.0004 
## scarsTRUE             3.68     0.35     10.63     0   
## downward_floorTRUE    0.89     0.36     2.52    0.01  
## tiltedTRUE            1.07     0.33     3.30   0.0005 
## septic_tankTRUE       -0.17    1.27     -0.13   0.45  
## conc_rainfallTRUE     1.90     0.58     3.29    0.001 
## wastewaterTRUE        0.72     0.24     3.01    0.001 
## ground_vegTRUE        0.85     0.25     3.34   0.0004 
## angleD                0.58     0.48     1.20    0.11  
## angleE                0.82     0.55     1.49    0.07  
## TC_saprolite_soilTRUE 0.25     0.29     0.86    0.19  
## R1| R2                1.00     0.91     1.10    0.14  
## R2| R3                5.33     0.96     5.56      0   
## R3| R4                10.39    1.05     9.88      0   
## ------------------------------------------------------

less p-value = 0.10 (TC_saprolitoTRUE,TaterroTRUE, DepTaludeAterroTRUE,DepTaludeAterroTRUE,landfillTRUE, construction_depositTRUE, leakTRUE)

par(mfrow=c(5,4))
plot.xmean.ordinaly (risk~ brick+ wood+ EN +  TC_mature_soil + T_construction + spring+ landfill+ leak+ garbage+ crack+ leaning_wall+ scars+ downward_floor+ tilted+ septic_tank+ conc_rainfall+ wastewater+ ground_veg + angle + TC_saprolite_soil
          ,data=train.data, cr=TRUE , subn=FALSE ,  cex.lab=1.5, cex.axis=2, cex.sub=2, cex.main=2)

Creating function with four level

Equation 1

sf <- function (y) {
        c('y>=1' = qlogis(mean(y>=1)),
          'y>=2' = qlogis(mean(y>=2)),
           'y>=3' = qlogis(mean(y>=3)),
            'y>=4' = qlogis(mean(y>=4)))
}

s<-with(train.data, summary(as.numeric(risk)~brick+ wood+ EN +  TC_mature_soil + T_construction + spring+ landfill+ leak+ garbage+ crack+ leaning_wall+ scars+ downward_floor+ tilted+ septic_tank+ conc_rainfall+ wastewater+ ground_veg + angle + TC_saprolite_soil
, fun=sf))
s
## as.numeric(risk)     N= 529 , 1 Missing 
## 
## +-----------------+---+---+----+----------+------------+----------+
## |                 |   |N  |y>=1|y>=2      |y>=3        |y>=4      |
## +-----------------+---+---+----+----------+------------+----------+
## |brick            |No | 38|Inf | 2.8903718| 1.673976434|-0.6539265|
## |                 |Yes|491|Inf | 2.2936565|-0.110090690|-2.0703091|
## +-----------------+---+---+----+----------+------------+----------+
## |wood             |No |456|Inf | 2.1875158|-0.175890666|-2.2881964|
## |                 |Yes| 73|Inf | 4.2766661| 1.192138347|-0.5920511|
## +-----------------+---+---+----+----------+------------+----------+
## |EN               |No |336|Inf | 1.8925642|-0.536304709|-2.6107090|
## |                 |Yes|193|Inf | 4.1484118| 0.971350509|-1.1905498|
## +-----------------+---+---+----+----------+------------+----------+
## |TC_mature_soil   |No |256|Inf | 1.8763169|-0.251314428|-2.2686835|
## |                 |Yes|273|Inf | 2.9957323| 0.228089975|-1.6495324|
## +-----------------+---+---+----+----------+------------+----------+
## |T_construction   |No |209|Inf | 1.5697727|-0.840471895|-3.2238634|
## |                 |Yes|320|Inf | 3.3354460| 0.524181415|-1.4663371|
## +-----------------+---+---+----+----------+------------+----------+
## |spring           |No |511|Inf | 2.2897370|-0.035228692|-2.0171228|
## |                 |Yes| 18|Inf |       Inf| 0.955511445|-0.2231436|
## +-----------------+---+---+----+----------+------------+----------+
## |landfill         |No |319|Inf | 1.8064656|-0.546093763|-2.7593435|
## |                 |Yes|210|Inf | 4.6443909| 0.847297860|-1.1895841|
## +-----------------+---+---+----+----------+------------+----------+
## |leak             |No |337|Inf | 1.9767874|-0.341561306|-2.4011368|
## |                 |Yes|192|Inf | 3.4339872| 0.600773860|-1.3350011|
## +-----------------+---+---+----+----------+------------+----------+
## |garbage          |No |352|Inf | 2.1118068|-0.205263126|-2.3374539|
## |                 |Yes|177|Inf | 2.9267394| 0.400759217|-1.3307245|
## +-----------------+---+---+----+----------+------------+----------+
## |crack            |No |436|Inf | 2.1620451|-0.352220594|-2.7178783|
## |                 |Yes| 93|Inf | 3.8177123| 2.233592222|-0.2376717|
## +-----------------+---+---+----+----------+------------+----------+
## |leaning_wall     |No |500|Inf | 2.2657445|-0.104093891|-2.0907411|
## |                 |Yes| 29|Inf |       Inf| 2.602689685|-0.2076394|
## +-----------------+---+---+----+----------+------------+----------+
## |scars            |No |329|Inf | 1.8168055|-1.290279708|-3.9858929|
## |                 |Yes|200|Inf | 5.2933048| 3.316780040|-0.8001193|
## +-----------------+---+---+----+----------+------------+----------+
## |downward_floor   |No |458|Inf | 2.1684456|-0.299154474|-2.3195142|
## |                 |Yes| 71|Inf |       Inf| 3.540959324|-0.4883528|
## +-----------------+---+---+----+----------+------------+----------+
## |tilted           |No |429|Inf | 2.1193936|-0.411296028|-2.5524648|
## |                 |Yes|100|Inf | 4.5951199| 2.586689344|-0.5322168|
## +-----------------+---+---+----+----------+------------+----------+
## |septic_tank      |No |525|Inf | 2.3194631|-0.011428696|-1.9221766|
## |                 |Yes|  4|Inf |       Inf| 1.098612289|-1.0986123|
## +-----------------+---+---+----+----------+------------+----------+
## |conc_rainfall    |No | 17|Inf |-0.6061358|-2.772588722|      -Inf|
## |                 |Yes|512|Inf | 2.5818989| 0.054701136|-1.8763169|
## +-----------------+---+---+----+----------+------------+----------+
## |wastewater       |No |204|Inf | 1.6094379|-0.521296924|-2.6873241|
## |                 |Yes|325|Inf | 3.1780538| 0.316461037|-1.5910888|
## +-----------------+---+---+----+----------+------------+----------+
## |ground_veg       |No |154|Inf | 1.2611312|-1.187165686|-2.6672282|
## |                 |Yes|375|Inf | 3.3266949| 0.438913042|-1.6984588|
## +-----------------+---+---+----+----------+------------+----------+
## |angle            |C  | 30|Inf |       Inf|-0.546543706|-3.3672958|
## |                 |D  |130|Inf | 3.7455748| 1.037987667|-1.0782034|
## |                 |E  |369|Inf | 1.9996355|-0.300340469|-2.2877700|
## +-----------------+---+---+----+----------+------------+----------+
## |TC_saprolite_soil|No |444|Inf | 2.2327613|-0.081125545|-1.9984156|
## |                 |Yes| 85|Inf | 3.0081548| 0.405465108|-1.5404450|
## +-----------------+---+---+----+----------+------------+----------+
## |Overall          |   |529|Inf | 2.3277965|-0.003780723|-1.9138903|
## +-----------------+---+---+----+----------+------------+----------+
plot(s, which=1:4, pch=1:4, xlab='logit', main=' ', xlim=c(-5,5), cex.lab=1, cex.axis=1, cex.sub=1)

Equation 2

  • parameters okay and so/so
  • porportion
  • excluded TC_geol_desf

f2 <- lrm(risk ~ angle + building + EN + TC_saprolito + Taterro + DepEncNatural + DepTaludeAterro + DepTaludeCorte + landfill + garbage + construction_deposit + crack + leaning_wall + scars + downward_floor +tilted + conc_rainfall_water + wastewater + leak + drainage + TC_mature_Soil + density + TC + tree +ground_veg + deforestation + banana , data=train.data, x=TRUE , y=TRUE)

      stargazer(anova(f2), type="text", style="default")
eq_OLR_02 <- polr(risk ~ brick+ wood+ EN+  TC_mature_soil+ T_construction+ landfill+ leak+ garbage+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ mixed+ conc_rainfall+ wastewater+ angle+ banana+ drainage+ TC_saprolite_soil+ TC+ deforestation,
                  
                 data= train.data
           ,  method = "logistic", Hess = TRUE)
ctable <- coef(summary(eq_OLR_02))








p<- pnorm(abs(ctable[, "t value"]), lower.tail = FALSE*2) #computes p value
ctable <- cbind(ctable, "p value" = p )

ctable
##                             Value Std. Error     t value      p value
## brickTRUE             -1.02669046  0.5363695 -1.91414777 2.780064e-02
## woodTRUE               1.32768210  0.3591081  3.69716521 1.090102e-04
## ENTRUE                 0.75195987  0.3894495  1.93082748 2.675220e-02
## TC_mature_soilTRUE     0.83948091  0.2400754  3.49673837 2.354918e-04
## T_constructionTRUE     0.34544537  0.3633729  0.95066349 1.708876e-01
## landfillTRUE           0.15897689  0.3319484  0.47892044 3.159976e-01
## leakTRUE              -0.46585461  0.2394543 -1.94548472 2.585833e-02
## garbageTRUE           -0.08051925  0.2914452 -0.27627580 3.911681e-01
## crackTRUE              2.18510247  0.3315992  6.58958895 2.205230e-11
## leaning_wallTRUE       1.84694552  0.5340813  3.45817297 2.719260e-04
## treeTRUE              -0.27362937  0.2436246 -1.12316005 1.306848e-01
## downward_floorTRUE     0.70251607  0.3600204  1.95132311 2.550931e-02
## tiltedTRUE             1.00138910  0.3283890  3.04939896 1.146499e-03
## ground_vegTRUE         0.74562688  0.2777504  2.68452118 3.631689e-03
## scarsTRUE              3.69680165  0.3535511 10.45620273 6.862313e-26
## mixedTRUE              0.13554685  0.5377497  0.25206308 4.004962e-01
## conc_rainfallTRUE      1.53156270  0.6140868  2.49404924 6.314751e-03
## wastewaterTRUE         0.49558891  0.2516271  1.96953739 2.444571e-02
## angleD                 0.38326490  0.4883057  0.78488726 2.162598e-01
## angleE                 0.64406825  0.5524103  1.16592379 1.218226e-01
## bananaTRUE             0.49509010  0.2622615  1.88777296 2.952822e-02
## drainage.L             0.94462156  0.2938619  3.21450794 6.533415e-04
## drainage.Q            -0.07284589  0.1913665 -0.38066164 3.517272e-01
## TC_saprolite_soilTRUE  0.22124220  0.3020933  0.73236391 2.319732e-01
## TCTRUE                -0.35016330  0.5379451 -0.65092753 2.575466e-01
## deforestationTRUE      0.27128912  0.4135792  0.65595440 2.559267e-01
## R1|R2                  0.01759417  1.1656514  0.01509385 4.939787e-01
## R2|R3                  4.56199525  1.1849084  3.85008267 5.903898e-05
## R3|R4                  9.69255339  1.2703103  7.63006767 1.173153e-14
stargazer((ctable), type="text", style="default", digits=2)
## 
## ======================================================
##                       Value Std. Error t value p value
## ------------------------------------------------------
## brickTRUE             -1.03    0.54     -1.91   0.03  
## woodTRUE              1.33     0.36     3.70   0.0001 
## ENTRUE                0.75     0.39     1.93    0.03  
## TC_mature_soilTRUE    0.84     0.24     3.50   0.0002 
## T_constructionTRUE    0.35     0.36     0.95    0.17  
## landfillTRUE          0.16     0.33     0.48    0.32  
## leakTRUE              -0.47    0.24     -1.95   0.03  
## garbageTRUE           -0.08    0.29     -0.28   0.39  
## crackTRUE             2.19     0.33     6.59      0   
## leaning_wallTRUE      1.85     0.53     3.46   0.0003 
## treeTRUE              -0.27    0.24     -1.12   0.13  
## downward_floorTRUE    0.70     0.36     1.95    0.03  
## tiltedTRUE            1.00     0.33     3.05    0.001 
## ground_vegTRUE        0.75     0.28     2.68    0.004 
## scarsTRUE             3.70     0.35     10.46     0   
## mixedTRUE             0.14     0.54     0.25    0.40  
## conc_rainfallTRUE     1.53     0.61     2.49    0.01  
## wastewaterTRUE        0.50     0.25     1.97    0.02  
## angleD                0.38     0.49     0.78    0.22  
## angleE                0.64     0.55     1.17    0.12  
## bananaTRUE            0.50     0.26     1.89    0.03  
## drainage.L            0.94     0.29     3.21    0.001 
## drainage.Q            -0.07    0.19     -0.38   0.35  
## TC_saprolite_soilTRUE 0.22     0.30     0.73    0.23  
## TCTRUE                -0.35    0.54     -0.65   0.26  
## deforestationTRUE     0.27     0.41     0.66    0.26  
## R1| R2                0.02     1.17     0.02    0.49  
## R2| R3                4.56     1.18     3.85   0.0001 
## R3| R4                9.69     1.27     7.63      0   
## ------------------------------------------------------
par(mfrow=c(6,4))
plot.xmean.ordinaly (risk~ brick+ wood+ EN+  TC_mature_soil+ T_construction+ landfill+ leak+ garbage+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ mixed+ conc_rainfall+ wastewater+ angle+ banana+ drainage+ TC_saprolite_soil+ TC+ deforestation
          ,data=train.data, cr=TRUE , subn=FALSE ,  cex.lab=1.5, cex.axis=4, cex.sub=4, cex.main=4)

sf <- function (y) {
        c('y>=1' = qlogis(mean(y>=1)),
          'y>=2' = qlogis(mean(y>=2)),
           'y>=3' = qlogis(mean(y>=3)),
            'y>=4' = qlogis(mean(y>=4)))
}

s<-with(train.data, summary(as.numeric(risk)~brick+ wood+ EN+  TC_mature_soil+ T_construction+ landfill+ leak+ garbage+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ mixed+ conc_rainfall+ wastewater+ angle+ banana+ drainage+ TC_saprolite_soil+ TC+ deforestation,data=train.data
, fun=sf))
s
## as.numeric(risk)     N= 529 , 1 Missing 
## 
## +-----------------+---+---+----+----------+------------+----------+
## |                 |   |N  |y>=1|y>=2      |y>=3        |y>=4      |
## +-----------------+---+---+----+----------+------------+----------+
## |brick            |No | 38|Inf | 2.8903718| 1.673976434|-0.6539265|
## |                 |Yes|491|Inf | 2.2936565|-0.110090690|-2.0703091|
## +-----------------+---+---+----+----------+------------+----------+
## |wood             |No |456|Inf | 2.1875158|-0.175890666|-2.2881964|
## |                 |Yes| 73|Inf | 4.2766661| 1.192138347|-0.5920511|
## +-----------------+---+---+----+----------+------------+----------+
## |EN               |No |336|Inf | 1.8925642|-0.536304709|-2.6107090|
## |                 |Yes|193|Inf | 4.1484118| 0.971350509|-1.1905498|
## +-----------------+---+---+----+----------+------------+----------+
## |TC_mature_soil   |No |256|Inf | 1.8763169|-0.251314428|-2.2686835|
## |                 |Yes|273|Inf | 2.9957323| 0.228089975|-1.6495324|
## +-----------------+---+---+----+----------+------------+----------+
## |T_construction   |No |209|Inf | 1.5697727|-0.840471895|-3.2238634|
## |                 |Yes|320|Inf | 3.3354460| 0.524181415|-1.4663371|
## +-----------------+---+---+----+----------+------------+----------+
## |landfill         |No |319|Inf | 1.8064656|-0.546093763|-2.7593435|
## |                 |Yes|210|Inf | 4.6443909| 0.847297860|-1.1895841|
## +-----------------+---+---+----+----------+------------+----------+
## |leak             |No |337|Inf | 1.9767874|-0.341561306|-2.4011368|
## |                 |Yes|192|Inf | 3.4339872| 0.600773860|-1.3350011|
## +-----------------+---+---+----+----------+------------+----------+
## |garbage          |No |352|Inf | 2.1118068|-0.205263126|-2.3374539|
## |                 |Yes|177|Inf | 2.9267394| 0.400759217|-1.3307245|
## +-----------------+---+---+----+----------+------------+----------+
## |crack            |No |436|Inf | 2.1620451|-0.352220594|-2.7178783|
## |                 |Yes| 93|Inf | 3.8177123| 2.233592222|-0.2376717|
## +-----------------+---+---+----+----------+------------+----------+
## |leaning_wall     |No |500|Inf | 2.2657445|-0.104093891|-2.0907411|
## |                 |Yes| 29|Inf |       Inf| 2.602689685|-0.2076394|
## +-----------------+---+---+----+----------+------------+----------+
## |tree             |No |203|Inf | 1.7917595|-0.555747311|-2.1594842|
## |                 |Yes|326|Inf | 2.8397280| 0.334369186|-1.7810642|
## +-----------------+---+---+----+----------+------------+----------+
## |downward_floor   |No |458|Inf | 2.1684456|-0.299154474|-2.3195142|
## |                 |Yes| 71|Inf |       Inf| 3.540959324|-0.4883528|
## +-----------------+---+---+----+----------+------------+----------+
## |tilted           |No |429|Inf | 2.1193936|-0.411296028|-2.5524648|
## |                 |Yes|100|Inf | 4.5951199| 2.586689344|-0.5322168|
## +-----------------+---+---+----+----------+------------+----------+
## |ground_veg       |No |154|Inf | 1.2611312|-1.187165686|-2.6672282|
## |                 |Yes|375|Inf | 3.3266949| 0.438913042|-1.6984588|
## +-----------------+---+---+----+----------+------------+----------+
## |scars            |No |329|Inf | 1.8168055|-1.290279708|-3.9858929|
## |                 |Yes|200|Inf | 5.2933048| 3.316780040|-0.8001193|
## +-----------------+---+---+----+----------+------------+----------+
## |mixed            |No |489|Inf | 2.2891621|-0.102338713|-2.0253743|
## |                 |Yes| 40|Inf | 2.9444390| 1.386294361|-0.9694006|
## +-----------------+---+---+----+----------+------------+----------+
## |conc_rainfall    |No | 17|Inf |-0.6061358|-2.772588722|      -Inf|
## |                 |Yes|512|Inf | 2.5818989| 0.054701136|-1.8763169|
## +-----------------+---+---+----+----------+------------+----------+
## |wastewater       |No |204|Inf | 1.6094379|-0.521296924|-2.6873241|
## |                 |Yes|325|Inf | 3.1780538| 0.316461037|-1.5910888|
## +-----------------+---+---+----+----------+------------+----------+
## |angle            |C  | 30|Inf |       Inf|-0.546543706|-3.3672958|
## |                 |D  |130|Inf | 3.7455748| 1.037987667|-1.0782034|
## |                 |E  |369|Inf | 1.9996355|-0.300340469|-2.2877700|
## +-----------------+---+---+----+----------+------------+----------+
## |banana           |No |354|Inf | 1.9785928|-0.377294231|-2.1785324|
## |                 |Yes|175|Inf | 3.7553692| 0.780158558|-1.4971087|
## +-----------------+---+---+----+----------+------------+----------+
## |drainage         |Y  | 70|Inf | 0.6505876|-2.047692843|-4.2341065|
## |                 |P  |226|Inf | 2.5091209|-0.582284588|-2.7963428|
## |                 |N  |233|Inf | 3.6331905| 1.104342963|-1.1984018|
## +-----------------+---+---+----+----------+------------+----------+
## |TC_saprolite_soil|No |444|Inf | 2.2327613|-0.081125545|-1.9984156|
## |                 |Yes| 85|Inf | 3.0081548| 0.405465108|-1.5404450|
## +-----------------+---+---+----+----------+------------+----------+
## |TC               |No | 28|Inf |       Inf| 1.098612289|-0.9162907|
## |                 |Yes|501|Inf | 2.2679496|-0.059898142|-1.9947003|
## +-----------------+---+---+----+----------+------------+----------+
## |deforestation    |No |493|Inf | 2.3480475| 0.052750565|-1.8497467|
## |                 |Yes| 36|Inf | 2.0794415|-0.820980552|-3.5553481|
## +-----------------+---+---+----+----------+------------+----------+
## |Overall          |   |529|Inf | 2.3277965|-0.003780723|-1.9138903|
## +-----------------+---+---+----+----------+------------+----------+
plot(s, which=1:4, pch=1:4, xlab='logit', main=' ', xlim=c(-5,5), cex.lab=1, cex.axis=2, cex.sub=1)

Equation 3

  • parameters okay and so/so
  • porportion
  • p-value based equation 2 > 0.5

f3 <- lrm(risk ~ angle +building + EN + DepTaludeAterro+ DepTaludeCorte+ crack+ leaning_wall+ scars+ downward_floor+ tilted+ conc_rainfall_water+ wastewater+ tree + TC , data=train.data, x=TRUE , y=TRUE) stargazer(anova(f3), type=“text”, style=“default”)

# x=TRUE, y=TRUE used by resid() below 

eq_OLR_03 <- polr(risk ~ wood+  TC_mature_soil+ T_construction+ landfill+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana+ drainage, data=train.data
           ,  method = "logistic", Hess = TRUE)
ctable <- coef(summary(eq_OLR_03))


p<- pnorm(abs(ctable[, "t value"]), lower.tail = FALSE*2) #computes p value
ctable <- cbind(ctable, "p value" = p )

ctable
##                          Value Std. Error    t value      p value
## woodTRUE            1.35991301  0.3326674  4.0879060 2.176422e-05
## TC_mature_soilTRUE  0.77425875  0.2247845  3.4444486 2.861127e-04
## T_constructionTRUE  0.29033617  0.2986494  0.9721639 1.654845e-01
## landfillTRUE        0.20245697  0.2941304  0.6883238 2.456244e-01
## crackTRUE           2.16094221  0.3210591  6.7306680 8.444298e-12
## leaning_wallTRUE    1.98344090  0.5332303  3.7196700 9.974160e-05
## treeTRUE           -0.22457958  0.2343787 -0.9581911 1.689832e-01
## downward_floorTRUE  0.58166083  0.3491176  1.6660886 4.784789e-02
## tiltedTRUE          1.07007476  0.3226381  3.3166409 4.555331e-04
## ground_vegTRUE      0.78040616  0.2698512  2.8919866 1.914072e-03
## scarsTRUE           3.63536564  0.3462412 10.4995190 4.341068e-26
## conc_rainfallTRUE   1.54725335  0.6022297  2.5692079 5.096565e-03
## wastewaterTRUE      0.42852562  0.2423058  1.7685321 3.848599e-02
## bananaTRUE          0.52589991  0.2502686  2.1013420 1.780548e-02
## drainage.L          0.95019610  0.2862648  3.3192911 4.512314e-04
## drainage.Q         -0.02802977  0.1881813 -0.1489509 4.407962e-01
## R1|R2               0.74011047  0.5938268  1.2463407 1.063197e-01
## R2|R3               5.14352621  0.6508105  7.9032627 1.358481e-15
## R3|R4              10.14786211  0.7909758 12.8295489 5.600720e-38
stargazer((ctable), type="text", style="default", digits = 2)
## 
## ===================================================
##                    Value Std. Error t value p value
## ---------------------------------------------------
## woodTRUE           1.36     0.33     4.09   0.0000 
## TC_mature_soilTRUE 0.77     0.22     3.44   0.0003 
## T_constructionTRUE 0.29     0.30     0.97    0.17  
## landfillTRUE       0.20     0.29     0.69    0.25  
## crackTRUE          2.16     0.32     6.73      0   
## leaning_wallTRUE   1.98     0.53     3.72   0.0001 
## treeTRUE           -0.22    0.23     -0.96   0.17  
## downward_floorTRUE 0.58     0.35     1.67    0.05  
## tiltedTRUE         1.07     0.32     3.32   0.0005 
## ground_vegTRUE     0.78     0.27     2.89    0.002 
## scarsTRUE          3.64     0.35     10.50     0   
## conc_rainfallTRUE  1.55     0.60     2.57    0.01  
## wastewaterTRUE     0.43     0.24     1.77    0.04  
## bananaTRUE         0.53     0.25     2.10    0.02  
## drainage.L         0.95     0.29     3.32   0.0005 
## drainage.Q         -0.03    0.19     -0.15   0.44  
## R1| R2             0.74     0.59     1.25    0.11  
## R2| R3             5.14     0.65     7.90      0   
## R3| R4             10.15    0.79     12.83     0   
## ---------------------------------------------------
#print (f3 , latex =TRUE , coefs =5)
par(mfrow=c(3,5))
plot.xmean.ordinaly (risk ~  wood+  TC_mature_soil+ T_construction+ landfill+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana+ drainage,,
          data=train.data, cr=TRUE , subn=FALSE , cex.points =0.65)

sf <- function (y) {
        c('y>=1' = qlogis(mean(y>=1)),
          'y>=2' = qlogis(mean(y>=2)),
           'y>=3' = qlogis(mean(y>=3)),
            'y>=4' = qlogis(mean(y>=4)))
}

s<-with(train.data, summary(as.numeric(risk)~wood+  TC_mature_soil+ T_construction+ landfill+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana+ drainage, fun=sf))
s
## as.numeric(risk)     N= 529 , 1 Missing 
## 
## +--------------+---+---+----+----------+------------+----------+
## |              |   |N  |y>=1|y>=2      |y>=3        |y>=4      |
## +--------------+---+---+----+----------+------------+----------+
## |wood          |No |456|Inf | 2.1875158|-0.175890666|-2.2881964|
## |              |Yes| 73|Inf | 4.2766661| 1.192138347|-0.5920511|
## +--------------+---+---+----+----------+------------+----------+
## |TC_mature_soil|No |256|Inf | 1.8763169|-0.251314428|-2.2686835|
## |              |Yes|273|Inf | 2.9957323| 0.228089975|-1.6495324|
## +--------------+---+---+----+----------+------------+----------+
## |T_construction|No |209|Inf | 1.5697727|-0.840471895|-3.2238634|
## |              |Yes|320|Inf | 3.3354460| 0.524181415|-1.4663371|
## +--------------+---+---+----+----------+------------+----------+
## |landfill      |No |319|Inf | 1.8064656|-0.546093763|-2.7593435|
## |              |Yes|210|Inf | 4.6443909| 0.847297860|-1.1895841|
## +--------------+---+---+----+----------+------------+----------+
## |crack         |No |436|Inf | 2.1620451|-0.352220594|-2.7178783|
## |              |Yes| 93|Inf | 3.8177123| 2.233592222|-0.2376717|
## +--------------+---+---+----+----------+------------+----------+
## |leaning_wall  |No |500|Inf | 2.2657445|-0.104093891|-2.0907411|
## |              |Yes| 29|Inf |       Inf| 2.602689685|-0.2076394|
## +--------------+---+---+----+----------+------------+----------+
## |tree          |No |203|Inf | 1.7917595|-0.555747311|-2.1594842|
## |              |Yes|326|Inf | 2.8397280| 0.334369186|-1.7810642|
## +--------------+---+---+----+----------+------------+----------+
## |downward_floor|No |458|Inf | 2.1684456|-0.299154474|-2.3195142|
## |              |Yes| 71|Inf |       Inf| 3.540959324|-0.4883528|
## +--------------+---+---+----+----------+------------+----------+
## |tilted        |No |429|Inf | 2.1193936|-0.411296028|-2.5524648|
## |              |Yes|100|Inf | 4.5951199| 2.586689344|-0.5322168|
## +--------------+---+---+----+----------+------------+----------+
## |ground_veg    |No |154|Inf | 1.2611312|-1.187165686|-2.6672282|
## |              |Yes|375|Inf | 3.3266949| 0.438913042|-1.6984588|
## +--------------+---+---+----+----------+------------+----------+
## |scars         |No |329|Inf | 1.8168055|-1.290279708|-3.9858929|
## |              |Yes|200|Inf | 5.2933048| 3.316780040|-0.8001193|
## +--------------+---+---+----+----------+------------+----------+
## |conc_rainfall |No | 17|Inf |-0.6061358|-2.772588722|      -Inf|
## |              |Yes|512|Inf | 2.5818989| 0.054701136|-1.8763169|
## +--------------+---+---+----+----------+------------+----------+
## |wastewater    |No |204|Inf | 1.6094379|-0.521296924|-2.6873241|
## |              |Yes|325|Inf | 3.1780538| 0.316461037|-1.5910888|
## +--------------+---+---+----+----------+------------+----------+
## |banana        |No |354|Inf | 1.9785928|-0.377294231|-2.1785324|
## |              |Yes|175|Inf | 3.7553692| 0.780158558|-1.4971087|
## +--------------+---+---+----+----------+------------+----------+
## |drainage      |Y  | 70|Inf | 0.6505876|-2.047692843|-4.2341065|
## |              |P  |226|Inf | 2.5091209|-0.582284588|-2.7963428|
## |              |N  |233|Inf | 3.6331905| 1.104342963|-1.1984018|
## +--------------+---+---+----+----------+------------+----------+
## |Overall       |   |529|Inf | 2.3277965|-0.003780723|-1.9138903|
## +--------------+---+---+----+----------+------------+----------+
plot(s, which=1:4, pch=1:4, xlab='logit', main=' ', xlim=c(-5,5), cex.lab=0.6, cex.axis=0.6, cex.sub=0.6)

Equation 4

  • p-value equation 3 > 0.05 (banana, DepTaludeCorte)
  • consider proportion
  • paremeters okay & so/so
  • fashion order

f4 <- lrm(risk ~ building + EN
+ DepEncNatural
+ crack + leaning_wall + scars + downward_floor +tilted + conc_rainfall_water + wastewater + drainage + TC_mature_Soil + TC + +ground_veg
,data=train.data, x=TRUE , y=TRUE) # x=TRUE, y=TRUE used by resid() below #print (f4 , latex =TRUE , coefs =5) stargazer(anova(f4), type=“text”, style=“default”)

eq_OLR_04 <- polr(risk~ wood+  TC_mature_soil+ T_construction+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana+ drainage
                  , data= train.data
           ,  method = "logistic", Hess = TRUE)
p<- pnorm(abs(ctable[, "t value"]), lower.tail = FALSE*2) #computes p value

ctable <- coef(summary(eq_OLR_04))

ctable <- cbind(ctable, "p value" = p )
## Warning in cbind(ctable, `p value` = p): number of rows of result is not a
## multiple of vector length (arg 2)
ctable
##                          Value Std. Error    t value      p value
## woodTRUE            1.35166967  0.3317656  4.0741701 2.176422e-05
## TC_mature_soilTRUE  0.75338776  0.2226474  3.3837713 2.861127e-04
## T_constructionTRUE  0.41586308  0.2365444  1.7580762 1.654845e-01
## crackTRUE           2.17799813  0.3202647  6.8006177 2.456244e-01
## leaning_wallTRUE    1.98732218  0.5341801  3.7203227 8.444298e-12
## treeTRUE           -0.23340945  0.2338978 -0.9979120 9.974160e-05
## downward_floorTRUE  0.60394229  0.3474590  1.7381687 1.689832e-01
## tiltedTRUE          1.10583488  0.3183037  3.4741506 4.784789e-02
## ground_vegTRUE      0.79280380  0.2691426  2.9456646 4.555331e-04
## scarsTRUE           3.62781314  0.3456558 10.4954489 1.914072e-03
## conc_rainfallTRUE   1.55984002  0.6028852  2.5872918 4.341068e-26
## wastewaterTRUE      0.39802182  0.2384409  1.6692682 5.096565e-03
## bananaTRUE          0.52472732  0.2502286  2.0969915 3.848599e-02
## drainage.L          0.96780556  0.2853833  3.3912486 1.780548e-02
## drainage.Q         -0.02460395  0.1881032 -0.1308003 4.512314e-04
## R1|R2               0.73750157  0.5948562  1.2397981 4.407962e-01
## R2|R3               5.14063995  0.6516730  7.8883739 1.063197e-01
## R3|R4              10.13233558  0.7905484 12.8168434 1.358481e-15
stargazer((ctable), type="text", style="default", digits=2)
## 
## ===================================================
##                    Value Std. Error t value p value
## ---------------------------------------------------
## woodTRUE           1.35     0.33     4.07   0.0000 
## TC_mature_soilTRUE 0.75     0.22     3.38   0.0003 
## T_constructionTRUE 0.42     0.24     1.76    0.17  
## crackTRUE          2.18     0.32     6.80    0.25  
## leaning_wallTRUE   1.99     0.53     3.72      0   
## treeTRUE           -0.23    0.23     -1.00  0.0001 
## downward_floorTRUE 0.60     0.35     1.74    0.17  
## tiltedTRUE         1.11     0.32     3.47    0.05  
## ground_vegTRUE     0.79     0.27     2.95   0.0005 
## scarsTRUE          3.63     0.35     10.50   0.002 
## conc_rainfallTRUE  1.56     0.60     2.59      0   
## wastewaterTRUE     0.40     0.24     1.67    0.01  
## bananaTRUE         0.52     0.25     2.10    0.04  
## drainage.L         0.97     0.29     3.39    0.02  
## drainage.Q         -0.02    0.19     -0.13  0.0005 
## R1| R2             0.74     0.59     1.24    0.44  
## R2| R3             5.14     0.65     7.89    0.11  
## R3| R4             10.13    0.79     12.82     0   
## ---------------------------------------------------
par(mfrow=c(4,4))
plot.xmean.ordinaly (risk ~  wood+  TC_mature_soil+ T_construction+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana+ drainage
          ,data=train.data, cr=TRUE , subn=FALSE , cex.points =0.65)

sf <- function (y) {
        c('y>=1' = qlogis(mean(y>=1)),
          'y>=2' = qlogis(mean(y>=2)),
           'y>=3' = qlogis(mean(y>=3)),
            'y>=4' = qlogis(mean(y>=4)))
}

s<-with(train.data, summary(as.numeric(risk)~wood+  TC_mature_soil+ T_construction+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana+ drainage
, fun=sf))
s
## as.numeric(risk)     N= 529 , 1 Missing 
## 
## +--------------+---+---+----+----------+------------+----------+
## |              |   |N  |y>=1|y>=2      |y>=3        |y>=4      |
## +--------------+---+---+----+----------+------------+----------+
## |wood          |No |456|Inf | 2.1875158|-0.175890666|-2.2881964|
## |              |Yes| 73|Inf | 4.2766661| 1.192138347|-0.5920511|
## +--------------+---+---+----+----------+------------+----------+
## |TC_mature_soil|No |256|Inf | 1.8763169|-0.251314428|-2.2686835|
## |              |Yes|273|Inf | 2.9957323| 0.228089975|-1.6495324|
## +--------------+---+---+----+----------+------------+----------+
## |T_construction|No |209|Inf | 1.5697727|-0.840471895|-3.2238634|
## |              |Yes|320|Inf | 3.3354460| 0.524181415|-1.4663371|
## +--------------+---+---+----+----------+------------+----------+
## |crack         |No |436|Inf | 2.1620451|-0.352220594|-2.7178783|
## |              |Yes| 93|Inf | 3.8177123| 2.233592222|-0.2376717|
## +--------------+---+---+----+----------+------------+----------+
## |leaning_wall  |No |500|Inf | 2.2657445|-0.104093891|-2.0907411|
## |              |Yes| 29|Inf |       Inf| 2.602689685|-0.2076394|
## +--------------+---+---+----+----------+------------+----------+
## |tree          |No |203|Inf | 1.7917595|-0.555747311|-2.1594842|
## |              |Yes|326|Inf | 2.8397280| 0.334369186|-1.7810642|
## +--------------+---+---+----+----------+------------+----------+
## |downward_floor|No |458|Inf | 2.1684456|-0.299154474|-2.3195142|
## |              |Yes| 71|Inf |       Inf| 3.540959324|-0.4883528|
## +--------------+---+---+----+----------+------------+----------+
## |tilted        |No |429|Inf | 2.1193936|-0.411296028|-2.5524648|
## |              |Yes|100|Inf | 4.5951199| 2.586689344|-0.5322168|
## +--------------+---+---+----+----------+------------+----------+
## |ground_veg    |No |154|Inf | 1.2611312|-1.187165686|-2.6672282|
## |              |Yes|375|Inf | 3.3266949| 0.438913042|-1.6984588|
## +--------------+---+---+----+----------+------------+----------+
## |scars         |No |329|Inf | 1.8168055|-1.290279708|-3.9858929|
## |              |Yes|200|Inf | 5.2933048| 3.316780040|-0.8001193|
## +--------------+---+---+----+----------+------------+----------+
## |conc_rainfall |No | 17|Inf |-0.6061358|-2.772588722|      -Inf|
## |              |Yes|512|Inf | 2.5818989| 0.054701136|-1.8763169|
## +--------------+---+---+----+----------+------------+----------+
## |wastewater    |No |204|Inf | 1.6094379|-0.521296924|-2.6873241|
## |              |Yes|325|Inf | 3.1780538| 0.316461037|-1.5910888|
## +--------------+---+---+----+----------+------------+----------+
## |banana        |No |354|Inf | 1.9785928|-0.377294231|-2.1785324|
## |              |Yes|175|Inf | 3.7553692| 0.780158558|-1.4971087|
## +--------------+---+---+----+----------+------------+----------+
## |drainage      |Y  | 70|Inf | 0.6505876|-2.047692843|-4.2341065|
## |              |P  |226|Inf | 2.5091209|-0.582284588|-2.7963428|
## |              |N  |233|Inf | 3.6331905| 1.104342963|-1.1984018|
## +--------------+---+---+----+----------+------------+----------+
## |Overall       |   |529|Inf | 2.3277965|-0.003780723|-1.9138903|
## +--------------+---+---+----+----------+------------+----------+
plot(s, which=1:4, pch=1:4, xlab='logit', main=' ', xlim=c(-5,5), cex.lab=0.7, cex.axis=0.5, cex.sub=0.5)

Equation 5 - Based on Equation 1

  • based on Eq 1
  • less p-value > 0.10 (
# x=TRUE, y=TRUE used by resid() below 
#print (f1 , latex =TRUE , coefs =5)
#stargazer(anova(f1), type="text", style="default")

eq_OLR_05 <- polr(risk ~ brick+ wood+  TC_mature_soil+ T_construction+ crack+ leaning_wall+ scars+ downward_floor+ tilted+ conc_rainfall+ wastewater+ ground_veg,  data= train.data
           ,  method = "logistic", Hess = TRUE)

ctable <- coef(summary(eq_OLR_05))

p<- pnorm(abs(ctable[, "t value"]), lower.tail = FALSE*2) #computes p value
ctable <- cbind(ctable, "p value" = p )

ctable
##                         Value Std. Error    t value      p value
## brickTRUE          -0.9850046  0.4326272 -2.2767978 1.139915e-02
## woodTRUE            1.4450153  0.3286541  4.3967668 5.493764e-06
## TC_mature_soilTRUE  0.7720915  0.2202420  3.5056507 2.277462e-04
## T_constructionTRUE  0.4639386  0.2320871  1.9989849 2.280499e-02
## crackTRUE           2.0607687  0.3093914  6.6607181 1.362464e-11
## leaning_wallTRUE    1.7693571  0.5258046  3.3650468 3.826534e-04
## scarsTRUE           3.7125246  0.3432396 10.8161310 1.443546e-27
## downward_floorTRUE  0.8794954  0.3436356  2.5593836 5.242898e-03
## tiltedTRUE          1.2082221  0.3170486  3.8108419 6.924717e-05
## conc_rainfallTRUE   1.9189167  0.5692761  3.3708017 3.747490e-04
## wastewaterTRUE      0.5823996  0.2292793  2.5401310 5.540549e-03
## ground_vegTRUE      0.9830516  0.2412863  4.0742128 2.308513e-05
## R1|R2               0.4242758  0.7000447  0.6060697 2.722342e-01
## R2|R3               4.6406314  0.7545942  6.1498374 3.878120e-10
## R3|R4               9.5994396  0.8531531 11.2517196 1.135601e-29
stargazer((ctable), type="text", style="default", digits = 2)
## 
## ===================================================
##                    Value Std. Error t value p value
## ---------------------------------------------------
## brickTRUE          -0.99    0.43     -2.28   0.01  
## woodTRUE           1.45     0.33     4.40   0.0000 
## TC_mature_soilTRUE 0.77     0.22     3.51   0.0002 
## T_constructionTRUE 0.46     0.23     2.00    0.02  
## crackTRUE          2.06     0.31     6.66      0   
## leaning_wallTRUE   1.77     0.53     3.37   0.0004 
## scarsTRUE          3.71     0.34     10.82     0   
## downward_floorTRUE 0.88     0.34     2.56    0.01  
## tiltedTRUE         1.21     0.32     3.81   0.0001 
## conc_rainfallTRUE  1.92     0.57     3.37   0.0004 
## wastewaterTRUE     0.58     0.23     2.54    0.01  
## ground_vegTRUE     0.98     0.24     4.07   0.0000 
## R1| R2             0.42     0.70     0.61    0.27  
## R2| R3             4.64     0.75     6.15      0   
## R3| R4             9.60     0.85     11.25     0   
## ---------------------------------------------------
par(mfrow=c(3,4))
plot.xmean.ordinaly (risk ~  brick+ wood+  TC_mature_soil+ T_construction+ crack+ leaning_wall+ scars+ downward_floor+ tilted+ conc_rainfall+ wastewater+ ground_veg
          ,data=train.data, cr=TRUE , subn=FALSE , cex.points =0.65)

sf <- function (y) {
        c('y>=1' = qlogis(mean(y>=1)),
          'y>=2' = qlogis(mean(y>=2)),
           'y>=3' = qlogis(mean(y>=3)),
            'y>=4' = qlogis(mean(y>=4)))
}

s<-with(train.data, summary(as.numeric(risk)~brick+ wood+  TC_mature_soil+ T_construction+ crack+ leaning_wall+ scars+ downward_floor+ tilted+ conc_rainfall+ wastewater+ ground_veg
, fun=sf))
s
## as.numeric(risk)     N= 529 , 1 Missing 
## 
## +--------------+---+---+----+----------+------------+----------+
## |              |   |N  |y>=1|y>=2      |y>=3        |y>=4      |
## +--------------+---+---+----+----------+------------+----------+
## |brick         |No | 38|Inf | 2.8903718| 1.673976434|-0.6539265|
## |              |Yes|491|Inf | 2.2936565|-0.110090690|-2.0703091|
## +--------------+---+---+----+----------+------------+----------+
## |wood          |No |456|Inf | 2.1875158|-0.175890666|-2.2881964|
## |              |Yes| 73|Inf | 4.2766661| 1.192138347|-0.5920511|
## +--------------+---+---+----+----------+------------+----------+
## |TC_mature_soil|No |256|Inf | 1.8763169|-0.251314428|-2.2686835|
## |              |Yes|273|Inf | 2.9957323| 0.228089975|-1.6495324|
## +--------------+---+---+----+----------+------------+----------+
## |T_construction|No |209|Inf | 1.5697727|-0.840471895|-3.2238634|
## |              |Yes|320|Inf | 3.3354460| 0.524181415|-1.4663371|
## +--------------+---+---+----+----------+------------+----------+
## |crack         |No |436|Inf | 2.1620451|-0.352220594|-2.7178783|
## |              |Yes| 93|Inf | 3.8177123| 2.233592222|-0.2376717|
## +--------------+---+---+----+----------+------------+----------+
## |leaning_wall  |No |500|Inf | 2.2657445|-0.104093891|-2.0907411|
## |              |Yes| 29|Inf |       Inf| 2.602689685|-0.2076394|
## +--------------+---+---+----+----------+------------+----------+
## |scars         |No |329|Inf | 1.8168055|-1.290279708|-3.9858929|
## |              |Yes|200|Inf | 5.2933048| 3.316780040|-0.8001193|
## +--------------+---+---+----+----------+------------+----------+
## |downward_floor|No |458|Inf | 2.1684456|-0.299154474|-2.3195142|
## |              |Yes| 71|Inf |       Inf| 3.540959324|-0.4883528|
## +--------------+---+---+----+----------+------------+----------+
## |tilted        |No |429|Inf | 2.1193936|-0.411296028|-2.5524648|
## |              |Yes|100|Inf | 4.5951199| 2.586689344|-0.5322168|
## +--------------+---+---+----+----------+------------+----------+
## |conc_rainfall |No | 17|Inf |-0.6061358|-2.772588722|      -Inf|
## |              |Yes|512|Inf | 2.5818989| 0.054701136|-1.8763169|
## +--------------+---+---+----+----------+------------+----------+
## |wastewater    |No |204|Inf | 1.6094379|-0.521296924|-2.6873241|
## |              |Yes|325|Inf | 3.1780538| 0.316461037|-1.5910888|
## +--------------+---+---+----+----------+------------+----------+
## |ground_veg    |No |154|Inf | 1.2611312|-1.187165686|-2.6672282|
## |              |Yes|375|Inf | 3.3266949| 0.438913042|-1.6984588|
## +--------------+---+---+----+----------+------------+----------+
## |Overall       |   |529|Inf | 2.3277965|-0.003780723|-1.9138903|
## +--------------+---+---+----+----------+------------+----------+
plot(s, which=1:4, pch=1:4, xlab='logit', main=' ', xlim=c(-5,5), cex.lab=0.7, cex.axis=0.5, cex.sub=0.5)

OLR Equation 6

# x=TRUE, y=TRUE used by resid() below 
#print (f1 , latex =TRUE , coefs =5)
#stargazer(anova(f1), type="text", style="default")

eq_OLR_06 <- polr(risk ~ brick+ wood+ mixed+ EN+ TC+ T_construction+ landfill+ leak+ garbage+ crack+ leaning_wall+ tree+ tilted+ angle+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana,  data= train.data
           ,  method = "logistic", Hess = TRUE)

ctable <- coef(summary(eq_OLR_06))

p<- pnorm(abs(ctable[, "t value"]), lower.tail = FALSE*2) #computes p value
ctable <- cbind(ctable, "p value" = p )

ctable
##                          Value Std. Error    t value      p value
## brickTRUE          -1.05807442  0.5285253 -2.0019372 2.264574e-02
## woodTRUE            1.29892967  0.3386960  3.8350906 6.275900e-05
## mixedTRUE           0.57075837  0.5211950  1.0950955 1.367374e-01
## ENTRUE              0.86131656  0.3778412  2.2795728 1.131652e-02
## TCTRUE              0.20240771  0.4996893  0.4050671 3.427141e-01
## T_constructionTRUE  0.41429074  0.3459415  1.1975745 1.155413e-01
## landfillTRUE        0.20302527  0.3160274  0.6424293 2.602972e-01
## leakTRUE           -0.25535721  0.2291285 -1.1144715 1.325385e-01
## garbageTRUE        -0.07754272  0.2815800 -0.2753843 3.915105e-01
## crackTRUE           2.12597279  0.3234234  6.5733425 2.459905e-11
## leaning_wallTRUE    1.88483397  0.5349106  3.5236431 2.128286e-04
## treeTRUE           -0.22435865  0.2344252 -0.9570587 1.692688e-01
## tiltedTRUE          1.09959958  0.3162272  3.4772453 2.532971e-04
## angleD              0.46250012  0.4808152  0.9619082 1.680478e-01
## angleE              0.74299695  0.5411633  1.3729625 8.488200e-02
## ground_vegTRUE      0.81085622  0.2660132  3.0481804 1.151158e-03
## scarsTRUE           3.75503123  0.3487101 10.7683454 2.428251e-27
## conc_rainfallTRUE   2.30702312  0.5851224  3.9428040 4.026724e-05
## wastewaterTRUE      0.58381729  0.2351919  2.4823018 6.526833e-03
## bananaTRUE          0.62345319  0.2546202  2.4485618 7.171392e-03
## R1|R2               1.27206162  1.1114680  1.1444878 1.262107e-01
## R2|R3               5.46625859  1.1478808  4.7620438 9.582105e-07
## R3|R4              10.45765911  1.2319906  8.4884242 1.047289e-17
stargazer((ctable), type="text", style="default", digits = 2)
## 
## ===================================================
##                    Value Std. Error t value p value
## ---------------------------------------------------
## brickTRUE          -1.06    0.53     -2.00   0.02  
## woodTRUE           1.30     0.34     3.84   0.0001 
## mixedTRUE          0.57     0.52     1.10    0.14  
## ENTRUE             0.86     0.38     2.28    0.01  
## TCTRUE             0.20     0.50     0.41    0.34  
## T_constructionTRUE 0.41     0.35     1.20    0.12  
## landfillTRUE       0.20     0.32     0.64    0.26  
## leakTRUE           -0.26    0.23     -1.11   0.13  
## garbageTRUE        -0.08    0.28     -0.28   0.39  
## crackTRUE          2.13     0.32     6.57      0   
## leaning_wallTRUE   1.88     0.53     3.52   0.0002 
## treeTRUE           -0.22    0.23     -0.96   0.17  
## tiltedTRUE         1.10     0.32     3.48   0.0003 
## angleD             0.46     0.48     0.96    0.17  
## angleE             0.74     0.54     1.37    0.08  
## ground_vegTRUE     0.81     0.27     3.05    0.001 
## scarsTRUE          3.76     0.35     10.77     0   
## conc_rainfallTRUE  2.31     0.59     3.94   0.0000 
## wastewaterTRUE     0.58     0.24     2.48    0.01  
## bananaTRUE         0.62     0.25     2.45    0.01  
## R1| R2             1.27     1.11     1.14    0.13  
## R2| R3             5.47     1.15     4.76   0.0000 
## R3| R4             10.46    1.23     8.49      0   
## ---------------------------------------------------
par(mfrow=c(5,4))
plot.xmean.ordinaly (risk ~  brick+ wood+ mixed+ EN+ TC+ T_construction+ landfill+ leak+ garbage+ crack+ leaning_wall+ tree+ tilted+ angle+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana
          ,data=train.data, cr=TRUE , subn=FALSE , cex.points =0.65)

sf <- function (y) {
        c('y>=1' = qlogis(mean(y>=1)),
          'y>=2' = qlogis(mean(y>=2)),
           'y>=3' = qlogis(mean(y>=3)),
            'y>=4' = qlogis(mean(y>=4)))
}

s<-with(train.data, summary(as.numeric(risk)~brick+ wood+ mixed+ EN+ TC+ T_construction+ landfill+ leak+ garbage+ crack+ leaning_wall+ tree+ tilted+ angle+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana
, fun=sf))
s
## as.numeric(risk)     N= 529 , 1 Missing 
## 
## +--------------+---+---+----+----------+------------+----------+
## |              |   |N  |y>=1|y>=2      |y>=3        |y>=4      |
## +--------------+---+---+----+----------+------------+----------+
## |brick         |No | 38|Inf | 2.8903718| 1.673976434|-0.6539265|
## |              |Yes|491|Inf | 2.2936565|-0.110090690|-2.0703091|
## +--------------+---+---+----+----------+------------+----------+
## |wood          |No |456|Inf | 2.1875158|-0.175890666|-2.2881964|
## |              |Yes| 73|Inf | 4.2766661| 1.192138347|-0.5920511|
## +--------------+---+---+----+----------+------------+----------+
## |mixed         |No |489|Inf | 2.2891621|-0.102338713|-2.0253743|
## |              |Yes| 40|Inf | 2.9444390| 1.386294361|-0.9694006|
## +--------------+---+---+----+----------+------------+----------+
## |EN            |No |336|Inf | 1.8925642|-0.536304709|-2.6107090|
## |              |Yes|193|Inf | 4.1484118| 0.971350509|-1.1905498|
## +--------------+---+---+----+----------+------------+----------+
## |TC            |No | 28|Inf |       Inf| 1.098612289|-0.9162907|
## |              |Yes|501|Inf | 2.2679496|-0.059898142|-1.9947003|
## +--------------+---+---+----+----------+------------+----------+
## |T_construction|No |209|Inf | 1.5697727|-0.840471895|-3.2238634|
## |              |Yes|320|Inf | 3.3354460| 0.524181415|-1.4663371|
## +--------------+---+---+----+----------+------------+----------+
## |landfill      |No |319|Inf | 1.8064656|-0.546093763|-2.7593435|
## |              |Yes|210|Inf | 4.6443909| 0.847297860|-1.1895841|
## +--------------+---+---+----+----------+------------+----------+
## |leak          |No |337|Inf | 1.9767874|-0.341561306|-2.4011368|
## |              |Yes|192|Inf | 3.4339872| 0.600773860|-1.3350011|
## +--------------+---+---+----+----------+------------+----------+
## |garbage       |No |352|Inf | 2.1118068|-0.205263126|-2.3374539|
## |              |Yes|177|Inf | 2.9267394| 0.400759217|-1.3307245|
## +--------------+---+---+----+----------+------------+----------+
## |crack         |No |436|Inf | 2.1620451|-0.352220594|-2.7178783|
## |              |Yes| 93|Inf | 3.8177123| 2.233592222|-0.2376717|
## +--------------+---+---+----+----------+------------+----------+
## |leaning_wall  |No |500|Inf | 2.2657445|-0.104093891|-2.0907411|
## |              |Yes| 29|Inf |       Inf| 2.602689685|-0.2076394|
## +--------------+---+---+----+----------+------------+----------+
## |tree          |No |203|Inf | 1.7917595|-0.555747311|-2.1594842|
## |              |Yes|326|Inf | 2.8397280| 0.334369186|-1.7810642|
## +--------------+---+---+----+----------+------------+----------+
## |tilted        |No |429|Inf | 2.1193936|-0.411296028|-2.5524648|
## |              |Yes|100|Inf | 4.5951199| 2.586689344|-0.5322168|
## +--------------+---+---+----+----------+------------+----------+
## |angle         |C  | 30|Inf |       Inf|-0.546543706|-3.3672958|
## |              |D  |130|Inf | 3.7455748| 1.037987667|-1.0782034|
## |              |E  |369|Inf | 1.9996355|-0.300340469|-2.2877700|
## +--------------+---+---+----+----------+------------+----------+
## |ground_veg    |No |154|Inf | 1.2611312|-1.187165686|-2.6672282|
## |              |Yes|375|Inf | 3.3266949| 0.438913042|-1.6984588|
## +--------------+---+---+----+----------+------------+----------+
## |scars         |No |329|Inf | 1.8168055|-1.290279708|-3.9858929|
## |              |Yes|200|Inf | 5.2933048| 3.316780040|-0.8001193|
## +--------------+---+---+----+----------+------------+----------+
## |conc_rainfall |No | 17|Inf |-0.6061358|-2.772588722|      -Inf|
## |              |Yes|512|Inf | 2.5818989| 0.054701136|-1.8763169|
## +--------------+---+---+----+----------+------------+----------+
## |wastewater    |No |204|Inf | 1.6094379|-0.521296924|-2.6873241|
## |              |Yes|325|Inf | 3.1780538| 0.316461037|-1.5910888|
## +--------------+---+---+----+----------+------------+----------+
## |banana        |No |354|Inf | 1.9785928|-0.377294231|-2.1785324|
## |              |Yes|175|Inf | 3.7553692| 0.780158558|-1.4971087|
## +--------------+---+---+----+----------+------------+----------+
## |Overall       |   |529|Inf | 2.3277965|-0.003780723|-1.9138903|
## +--------------+---+---+----+----------+------------+----------+
plot(s, which=1:4, pch=1:4, xlab='logit', main=' ', xlim=c(-5,5), cex.lab=0.7, cex.axis=0.5, cex.sub=0.5)

Predicion on test data Eq 1: http://r-statistics.co/Ordinal-Logistic-Regression-With-R.html

predictedLevel1 <- predict(eq_OLR_01, test.data) # predict the levels directly

predictedScores1 <- predict(eq_OLR_01, test.data, type="p") 
 # predict the probabilites

## Confusion matrix and misclassification error
table(test.data$risk, predictedLevel1)
##     predictedLevel1
##      R1 R2 R3 R4
##   R1  3 16  0  0
##   R2  3 81  9  0
##   R3  0 17 57 10
##   R4  0  0 15 13
p1 <- mean(as.character(test.data$risk) != as.character(predictedLevel1)) #misclassification error
p1 
## [1] 0.3125

Predicion on test data Eq 2: http://r-statistics.co/Ordinal-Logistic-Regression-With-R.html

predictedLevel2 <- predict(eq_OLR_02, test.data) # predict the levels directly

## Confusion matrix and misclassification error
table(test.data$risk, predictedLevel2)
##     predictedLevel2
##      R1 R2 R3 R4
##   R1  3 16  0  0
##   R2  1 83  9  0
##   R3  0 17 54 13
##   R4  0  0 15 13
p2 <- mean(as.character(test.data$risk) != as.character(predictedLevel2))
p2
## [1] 0.3169643

Predicion on test data Eq 3: http://r-statistics.co/Ordinal-Logistic-Regression-With-R.html

predictedLevel3 <- predict(eq_OLR_03, test.data) # predict the levels directly

predictedScores1 <- predict(eq_OLR_03, test.data, type="p") 
 # predict the probabilites

## Confusion matrix and misclassification error
table(test.data$risk, predictedLevel3)
##     predictedLevel3
##      R1 R2 R3 R4
##   R1  3 16  0  0
##   R2  2 84  7  0
##   R3  0 18 56 10
##   R4  0  0 13 15
p3 <- mean(as.character(test.data$risk) != as.character(predictedLevel3))
p3
## [1] 0.2946429

Predicion on test data Eq 4: http://r-statistics.co/Ordinal-Logistic-Regression-With-R.html

predictedLevel4 <- predict(eq_OLR_04, test.data) # predict the levels directly

predictedScores1 <- predict(eq_OLR_04, test.data, type="p") 
 # predict the probabilites

## Confusion matrix and misclassification error
table(test.data$risk, predictedLevel4)
##     predictedLevel4
##      R1 R2 R3 R4
##   R1  3 16  0  0
##   R2  2 84  7  0
##   R3  0 18 56 10
##   R4  0  0 13 15
p4 <- mean(as.character(test.data$risk) != as.character(predictedLevel4))
p4
## [1] 0.2946429

Predicion on test data Eq 5: http://r-statistics.co/Ordinal-Logistic-Regression-With-R.html

predictedLevel5 <- predict(eq_OLR_05, test.data) # predict the levels directly

predictedScores5 <- predict(eq_OLR_05, test.data, type="p") 
 # predict the probabilites

## Confusion matrix and misclassification error
table(test.data$risk, predictedLevel5)
##     predictedLevel5
##      R1 R2 R3 R4
##   R1  3 16  0  0
##   R2  3 81  9  0
##   R3  0 16 59  9
##   R4  0  0 12 16
p5 <- mean(as.character(test.data$risk) != as.character(predictedLevel5))
p5
## [1] 0.2901786

Predicion on test data Eq 6: http://r-statistics.co/Ordinal-Logistic-Regression-With-R.html

predictedLevel6 <- predict(eq_OLR_06, test.data) # predict the levels directly

predictedScores6 <- predict(eq_OLR_06, test.data, type="p") 
 # predict the probabilites

## Confusion matrix and misclassification error
table(test.data$risk, predictedLevel6)
##     predictedLevel6
##      R1 R2 R3 R4
##   R1  3 16  0  0
##   R2  4 82  7  0
##   R3  0 19 51 14
##   R4  0  0 14 14
p6 <- mean(as.character(test.data$risk) != as.character(predictedLevel6))
p6
## [1] 0.3303571

Predicion on test data Eq 7: http://r-statistics.co/Ordinal-Logistic-Regression-With-R.html

#Table 

df2 <- data.frame(
  
  "Equations"=c(1:6), 
  "Predicted"=c(1-p1, 
                1-p2,
                1-p3,
                1-p4,
                1-p5,
                1-p6
               
              
    
    
  )
  
  
  
)

df2
##   Equations Predicted
## 1         1 0.6875000
## 2         2 0.6830357
## 3         3 0.7053571
## 4         4 0.7053571
## 5         5 0.7098214
## 6         6 0.6696429